Thesis (Ph.D.) - Cairo University - Faculty of Engineering - Department of Systems and Biomedical Engineering

Hepatocellular carcinoma(HCC) is a tumor of the liver which usually arises in the setting of chronic liver diseases. Fibrolamellar hepatocellular carcinoma (F- HCC) is a rare entity of HCC not yet analyzed cytogenetically. The use of high- performance parallel computing techniques can enable researchers to employ large numbers of processors to run comprehensive analyses within a reasonable period. This work provides a genomic study that focuses on using bioinformatics approaches to predict the molecular causes of HCC and F-HCC by the investigation whole genome sequence of the chromosomal aberrations using single nucleotide polymorphism (SNP)arrays and Next generation sequence (NGS) by applying four statistical techniques. The study revealed 3 distinct structural variations related genes MDM4, PRDM5, and WHSC1, these genes are a novel target signature that can help to predict survival of patients with detecting F-HCC. A new altered chromosome region amplification(4q22.1), this altered chromosomal region is novel for detect HCC, this finding has not previously reported being involved in liver carcinogenesis. NGS detect EPHA5, UBE1L2 tumor suppressor and UGT2B28 for both F-HCC and HCC

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